Research

PUBLICATIONS & RESEARCH TOPICS

Publications

30+ peer-reviewed publications, 800+ citations, h-index 13 |ORCID: 0000-0002-6996-0734

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Research Topics

SUPER-SENSITIVE WAVE-FRONT SENSING

 

We develop ideas on

  • Super-sensitive wave-front sensors. We're currently integrating a pyramid (modulated) in our lab
  • Non-linear wave-front sensing. Give linearity away, reach out to new sensitivity realms
  • Spot-shrinkage for elongated laser-guide stars wave-front sensing on existing detectors

 

POST-PROCESSING AO-CORRECTED TELEMETRY/PSF RECONSTRUCTON

Post-processing of partially corrected AO data is an Achilles' heel for the reconstruction of the PSF is an extremely complex task to accomplish, already in classical AO, let alone wide-field.

Currently we're developing software classes to

  • Reconstruct PSF out of tomographic MOAO systems
  • Provide Keck Observatory with a PSF reconstruction pipeline for the NGS and LGS modes
  • Pursuing reserach leading to a working pipeline for the AOF's MUSE instrument in wide and narrow field modes
  • Collaborating with NRC's Herzberg  Intitute of Astrophysics in support of PSF reconstruction for LTAO systems (-> useful for out Harmoni project)
  • Collaborating with TMT PO on their effort to perform PSF reconstruction with MCAO systems

 

 

ADVANCED TOMOGRAPHY RECONSTRUCTION METHODS

 

Turn-key AO requires robustness to operate 100% of the time at full performance. To that end new processing architectures are needed to tackle the curse of dimensionality (scaling with the fourth power of the telescope diameter D⁴) whilst making efficient use of combined LGS and NGS measurements in any of the WFAO modes. We are acquiring expertise and leading efforts in

  • Fast wave-front reconstruction in the spatial-frequency domain
  • Multi-time-step tomographic reconstruction
  • Iterative, large-scale tomographic reconstruction
  • Kalman filters for large number of degrees-of-freedom architectures

 

MODELLING SOFTWARE DEVELOPMENT

 

We support the development of OOMAO, an Object-oriented Matlab Adaptive Optics library of Matlab R ⃝classes.

Objects from the different classes are assembled to perform the numerical modeling of Adaptive Optics systems. OOMAO can be seen as an extension of the Matlab R ⃝ language. Overloaded Matlab R ⃝ operators are used to propagate the wavefront through the system and to update object properties.

Public and private, version-controlled repositories can be found here

  • OOMAO (Public)
  • OOMAO (Private) : This repository is intended for internal development in LAM.

I strongly encourage the community to give it a try. It's licence-free and free-of-charge. As a future user, you're welcome to add to it and to become an official co-developer. Please drop me an email.

Past workshops

  • Tools for Adaptive Optics Simulations on ELTs >>

ATMOSPHERIC PARAMETER CHARACTERISATION AND IDENTIFICAITON

 

Atmospheric parameter identification is paramount for the runtime optimisation of tomography and the post-processing of AO telemetry.

 

Past workshops

  • Atmospheric parameter characterisation and identification >>

PHASE-DIVERSITY FOR SYSTEM CALIBRATION

 

As part of our running collaborations, we've hosted Masen Lamb, PhD student at UVic for 4 months (Mar-Jun 2016) to develop phase-diversity algorithms for AO systems calibration. These are now being applied to

  • Fine co-phasing of segmented telescopes
  • Off-line calibration of non-comon path aberrations
  • Calibration of low-wind-effect

 

CONTACT DETAILS


Porto

PORTUGAL


cmcorreia_at_spaceodt.net


Tel: +33 4 91 05 59 00

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